Overview

Dataset statistics

Number of variables11
Number of observations1000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory86.1 KiB
Average record size in memory88.1 B

Variable types

NUM10
BOOL1

Warnings

X0 has unique values Unique
X1 has unique values Unique
X2 has unique values Unique
X3 has unique values Unique
X4 has unique values Unique
X5 has unique values Unique
X6 has unique values Unique
X7 has unique values Unique
X8 has unique values Unique
X9 has unique values Unique

Reproduction

Analysis started2020-12-15 20:11:05.384003
Analysis finished2020-12-15 20:11:28.927689
Duration23.54 seconds
Software versionpandas-profiling v2.9.0
Download configurationconfig.yaml

Variables

X0
Real number (ℝ)

UNIQUE

Distinct1000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-0.02778450552
Minimum-3.048372494
Maximum2.746622549
Zeros0
Zeros (%)0.0%
Memory size7.9 KiB
2020-12-15T21:11:29.032573image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum-3.048372494
5-th percentile-1.638485668
Q1-0.7082919408
median-0.04342463918
Q30.6435376299
95-th percentile1.636872198
Maximum2.746622549
Range5.794995043
Interquartile range (IQR)1.351829571

Descriptive statistics

Standard deviation0.9962005462
Coefficient of variation (CV)-35.85453574
Kurtosis-0.2376674873
Mean-0.02778450552
Median Absolute Deviation (MAD)0.6736279063
Skewness0.06782106709
Sum-27.78450552
Variance0.9924155282
MonotocityNot monotonic
2020-12-15T21:11:29.241675image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
1.35122052210.1%
 
-0.0215794958510.1%
 
1.002483210.1%
 
0.445787804710.1%
 
-0.469800016610.1%
 
-0.427119695210.1%
 
0.480789015310.1%
 
1.57031111510.1%
 
1.63418197510.1%
 
0.48175353710.1%
 
0.699377316910.1%
 
0.387594213910.1%
 
1.93394126310.1%
 
-0.082253285210.1%
 
0.876681733310.1%
 
0.089060789610.1%
 
0.394501261410.1%
 
-0.0830640867910.1%
 
-0.336356502210.1%
 
0.361327796610.1%
 
0.684167825610.1%
 
0.718752394610.1%
 
-0.259150693410.1%
 
0.733440986210.1%
 
1.54389843210.1%
 
Other values (975)97597.5%
 
ValueCountFrequency (%) 
-3.04837249410.1%
 
-2.98611256910.1%
 
-2.53369855710.1%
 
-2.51269849710.1%
 
-2.46080993710.1%
 
-2.42467770210.1%
 
-2.39880839910.1%
 
-2.37961591610.1%
 
-2.35897725910.1%
 
-2.27189649510.1%
 
ValueCountFrequency (%) 
2.74662254910.1%
 
2.71429845610.1%
 
2.66199463210.1%
 
2.66169406810.1%
 
2.5129579410.1%
 
2.41768722510.1%
 
2.40729673710.1%
 
2.39733086110.1%
 
2.36587630110.1%
 
2.36348116610.1%
 

X1
Real number (ℝ)

UNIQUE

Distinct1000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-0.00312270938
Minimum-3.405002261
Maximum3.082483146
Zeros0
Zeros (%)0.0%
Memory size7.9 KiB
2020-12-15T21:11:29.466365image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum-3.405002261
5-th percentile-1.635703875
Q1-0.6480943339
median-0.01092986995
Q30.6392988632
95-th percentile1.690955834
Maximum3.082483146
Range6.487485407
Interquartile range (IQR)1.287393197

Descriptive statistics

Standard deviation1.004726347
Coefficient of variation (CV)-321.7482719
Kurtosis0.007456672639
Mean-0.00312270938
Median Absolute Deviation (MAD)0.6459058217
Skewness-0.007250373786
Sum-3.12270938
Variance1.009475032
MonotocityNot monotonic
2020-12-15T21:11:29.685782image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
-0.258362809810.1%
 
-1.29174332910.1%
 
-0.804721695510.1%
 
-0.478151519910.1%
 
-0.289896835810.1%
 
2.15677387210.1%
 
-0.129030198110.1%
 
0.0962695679810.1%
 
0.416975845510.1%
 
-0.540430450110.1%
 
-0.468929212910.1%
 
1.67239846910.1%
 
1.63428684110.1%
 
0.178454366410.1%
 
0.461763759510.1%
 
-0.199772359410.1%
 
0.505703653710.1%
 
-0.406583866210.1%
 
-0.379820949810.1%
 
0.244983628710.1%
 
0.892084090610.1%
 
0.27379973710.1%
 
-0.203269399910.1%
 
0.0616205366210.1%
 
0.556278970310.1%
 
Other values (975)97597.5%
 
ValueCountFrequency (%) 
-3.40500226110.1%
 
-2.97478125910.1%
 
-2.74884670910.1%
 
-2.71191801610.1%
 
-2.6722291110.1%
 
-2.58004748810.1%
 
-2.5065088510.1%
 
-2.46335500810.1%
 
-2.45626041610.1%
 
-2.45052501810.1%
 
ValueCountFrequency (%) 
3.08248314610.1%
 
2.66416812410.1%
 
2.65299268710.1%
 
2.62201394910.1%
 
2.6121584410.1%
 
2.48040321310.1%
 
2.43220772710.1%
 
2.43195854110.1%
 
2.36952215810.1%
 
2.33580625610.1%
 

X2
Real number (ℝ)

UNIQUE

Distinct1000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.01263469301
Minimum-2.86840252
Maximum3.150183135
Zeros0
Zeros (%)0.0%
Memory size7.9 KiB
2020-12-15T21:11:29.912661image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum-2.86840252
5-th percentile-1.656155409
Q1-0.6559330468
median-0.03023056714
Q30.7201110393
95-th percentile1.615863404
Maximum3.150183135
Range6.018585656
Interquartile range (IQR)1.376044086

Descriptive statistics

Standard deviation0.9878079642
Coefficient of variation (CV)78.1821896
Kurtosis-0.25734645
Mean0.01263469301
Median Absolute Deviation (MAD)0.6924423796
Skewness0.01637312968
Sum12.63469301
Variance0.9757645741
MonotocityNot monotonic
2020-12-15T21:11:30.128175image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
-0.273066080110.1%
 
0.413375517610.1%
 
-1.00689830610.1%
 
-0.885311520410.1%
 
-0.233181164210.1%
 
-1.51038473810.1%
 
0.205496132510.1%
 
0.821280658510.1%
 
-0.317189397910.1%
 
-0.878719165910.1%
 
-2.47223537310.1%
 
-0.196190711510.1%
 
0.177055889810.1%
 
-0.963922120810.1%
 
-0.602363221210.1%
 
0.261107515710.1%
 
2.12678353910.1%
 
-1.3310095910.1%
 
-1.79256941410.1%
 
-1.76772132510.1%
 
-0.141267459610.1%
 
2.76300902910.1%
 
1.58954007310.1%
 
-1.0379785410.1%
 
2.04776098910.1%
 
Other values (975)97597.5%
 
ValueCountFrequency (%) 
-2.8684025210.1%
 
-2.82754436210.1%
 
-2.64332662710.1%
 
-2.57539385310.1%
 
-2.47223537310.1%
 
-2.44726357810.1%
 
-2.36728490810.1%
 
-2.23259328910.1%
 
-2.21202790110.1%
 
-2.18699201310.1%
 
ValueCountFrequency (%) 
3.15018313510.1%
 
2.76300902910.1%
 
2.63108703510.1%
 
2.49887935210.1%
 
2.44867787510.1%
 
2.4006931610.1%
 
2.31405458510.1%
 
2.28484086910.1%
 
2.2650237710.1%
 
2.2032245610.1%
 

X3
Real number (ℝ)

UNIQUE

Distinct1000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-0.0236533156
Minimum-3.01944531
Maximum3.204445541
Zeros0
Zeros (%)0.0%
Memory size7.9 KiB
2020-12-15T21:11:30.348778image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum-3.01944531
5-th percentile-1.73754817
Q1-0.6713256936
median-0.02753355683
Q30.6543204141
95-th percentile1.587369599
Maximum3.204445541
Range6.223890851
Interquartile range (IQR)1.325646108

Descriptive statistics

Standard deviation1.012214808
Coefficient of variation (CV)-42.79378104
Kurtosis0.02408265296
Mean-0.0236533156
Median Absolute Deviation (MAD)0.6648659048
Skewness-0.04488037671
Sum-23.6533156
Variance1.024578818
MonotocityNot monotonic
2020-12-15T21:11:30.564770image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
0.520601166310.1%
 
1.23739797910.1%
 
0.17287616210.1%
 
-2.04408163810.1%
 
-1.87078814510.1%
 
0.510793931810.1%
 
-0.832731467110.1%
 
0.407500745710.1%
 
1.18127698910.1%
 
-0.635534337910.1%
 
0.62794956710.1%
 
0.0162913828510.1%
 
-0.589508104110.1%
 
-1.81994958710.1%
 
-0.981764744710.1%
 
0.874716940410.1%
 
-1.34778482610.1%
 
0.163509033810.1%
 
-0.513527517510.1%
 
-0.403211961110.1%
 
-0.844446726710.1%
 
0.182572492710.1%
 
2.24571841910.1%
 
-0.588637629310.1%
 
0.283722239510.1%
 
Other values (975)97597.5%
 
ValueCountFrequency (%) 
-3.0194453110.1%
 
-2.9815835710.1%
 
-2.94083559510.1%
 
-2.80917424210.1%
 
-2.68138178910.1%
 
-2.64425509610.1%
 
-2.60111809610.1%
 
-2.59778052310.1%
 
-2.59352824410.1%
 
-2.45918089910.1%
 
ValueCountFrequency (%) 
3.20444554110.1%
 
2.82524192610.1%
 
2.63204833710.1%
 
2.50933599610.1%
 
2.50838504210.1%
 
2.47806153410.1%
 
2.42741792410.1%
 
2.4253382210.1%
 
2.37677638210.1%
 
2.35383040910.1%
 

X4
Real number (ℝ)

UNIQUE

Distinct1000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-0.0006270512572
Minimum-3.032493254
Maximum2.876253778
Zeros0
Zeros (%)0.0%
Memory size7.9 KiB
2020-12-15T21:11:30.790050image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum-3.032493254
5-th percentile-1.642880464
Q1-0.6557655138
median-0.006845246771
Q30.6846467788
95-th percentile1.605376141
Maximum2.876253778
Range5.908747032
Interquartile range (IQR)1.340412293

Descriptive statistics

Standard deviation0.9905193146
Coefficient of variation (CV)-1579.646485
Kurtosis-0.1259770223
Mean-0.0006270512572
Median Absolute Deviation (MAD)0.6771186404
Skewness0.02293373589
Sum-0.6270512572
Variance0.9811285125
MonotocityNot monotonic
2020-12-15T21:11:31.134631image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
0.321066244210.1%
 
-0.892943388510.1%
 
0.87562841210.1%
 
1.56645540910.1%
 
0.879352823210.1%
 
-1.13798259210.1%
 
0.107948916310.1%
 
-0.396941158210.1%
 
-0.0845239428810.1%
 
0.16878567510.1%
 
1.82931492210.1%
 
-1.25377023810.1%
 
-1.38454988110.1%
 
1.36708310610.1%
 
-1.97944592510.1%
 
-1.37209825310.1%
 
-0.635636316310.1%
 
-1.89835385610.1%
 
0.48796293710.1%
 
-1.66649649510.1%
 
-1.54139742310.1%
 
1.64590333410.1%
 
-1.20011315210.1%
 
-0.882724270210.1%
 
0.585814740610.1%
 
Other values (975)97597.5%
 
ValueCountFrequency (%) 
-3.03249325410.1%
 
-2.84597901410.1%
 
-2.78101956410.1%
 
-2.63820606110.1%
 
-2.63312060310.1%
 
-2.48183431410.1%
 
-2.46965638910.1%
 
-2.40147904710.1%
 
-2.34195847210.1%
 
-2.24086272210.1%
 
ValueCountFrequency (%) 
2.87625377810.1%
 
2.85024745110.1%
 
2.82610224610.1%
 
2.71757399910.1%
 
2.63771031410.1%
 
2.57148298510.1%
 
2.49237969110.1%
 
2.42286566110.1%
 
2.34003911910.1%
 
2.28161532310.1%
 

X5
Real number (ℝ)

UNIQUE

Distinct1000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-0.001301243927
Minimum-3.307190939
Maximum2.983716183
Zeros0
Zeros (%)0.0%
Memory size7.9 KiB
2020-12-15T21:11:31.365173image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum-3.307190939
5-th percentile-1.557883621
Q1-0.6658131556
median-0.01628529755
Q30.676623154
95-th percentile1.6180387
Maximum2.983716183
Range6.290907122
Interquartile range (IQR)1.34243631

Descriptive statistics

Standard deviation0.9789171111
Coefficient of variation (CV)-752.2933178
Kurtosis-0.2019884186
Mean-0.001301243927
Median Absolute Deviation (MAD)0.673709609
Skewness0.09036720191
Sum-1.301243927
Variance0.9582787104
MonotocityNot monotonic
2020-12-15T21:11:31.574163image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
0.244756649910.1%
 
-1.16841663310.1%
 
0.982805408710.1%
 
-1.26741713610.1%
 
-0.642688655310.1%
 
0.391731505910.1%
 
0.78410457110.1%
 
-0.961530116910.1%
 
0.485120202410.1%
 
-1.61370861510.1%
 
-0.291866477110.1%
 
1.55950334410.1%
 
0.0802877916810.1%
 
-0.50308622310.1%
 
-1.22416497810.1%
 
1.73952278410.1%
 
0.19750420410.1%
 
0.0693644349210.1%
 
-0.705116646510.1%
 
-0.632144898210.1%
 
-0.992236076510.1%
 
-0.556879232410.1%
 
-0.223507076410.1%
 
-1.17992910610.1%
 
-0.520438192810.1%
 
Other values (975)97597.5%
 
ValueCountFrequency (%) 
-3.30719093910.1%
 
-2.50447233910.1%
 
-2.32541891410.1%
 
-2.28678934710.1%
 
-2.27997876710.1%
 
-2.25260126910.1%
 
-2.24563160210.1%
 
-2.20537247910.1%
 
-2.19943937410.1%
 
-2.19017536110.1%
 
ValueCountFrequency (%) 
2.98371618310.1%
 
2.82100000510.1%
 
2.58208402710.1%
 
2.53361221610.1%
 
2.51603680410.1%
 
2.45246210110.1%
 
2.44994768510.1%
 
2.4024251210.1%
 
2.36915139310.1%
 
2.34900817310.1%
 

X6
Real number (ℝ)

UNIQUE

Distinct1000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.03673386662
Minimum-2.823511165
Maximum3.566580347
Zeros0
Zeros (%)0.0%
Memory size7.9 KiB
2020-12-15T21:11:31.789111image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum-2.823511165
5-th percentile-1.602296929
Q1-0.6341860017
median0.05706662317
Q30.7130017238
95-th percentile1.604049349
Maximum3.566580347
Range6.390091512
Interquartile range (IQR)1.347187725

Descriptive statistics

Standard deviation0.9855826153
Coefficient of variation (CV)26.83035319
Kurtosis0.04233541497
Mean0.03673386662
Median Absolute Deviation (MAD)0.6681969808
Skewness-0.02140640892
Sum36.73386662
Variance0.9713730916
MonotocityNot monotonic
2020-12-15T21:11:32.002960image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
-0.883529261310.1%
 
-1.49951731710.1%
 
0.478799952210.1%
 
0.0550896826810.1%
 
0.301154664510.1%
 
-0.262106688910.1%
 
-0.205126300810.1%
 
0.0840999742710.1%
 
-0.136779699310.1%
 
0.301230093710.1%
 
1.37145079610.1%
 
0.861033077810.1%
 
1.19732107110.1%
 
0.722571013910.1%
 
0.271646563710.1%
 
-0.671045047610.1%
 
-0.046808564910.1%
 
-0.984148593810.1%
 
-1.71727415810.1%
 
-1.85778908110.1%
 
0.173137650610.1%
 
-0.215946741710.1%
 
-0.930603161210.1%
 
0.217305017310.1%
 
0.629436141110.1%
 
Other values (975)97597.5%
 
ValueCountFrequency (%) 
-2.82351116510.1%
 
-2.78381494710.1%
 
-2.76229923410.1%
 
-2.67881578310.1%
 
-2.5838684210.1%
 
-2.58112537910.1%
 
-2.43816260610.1%
 
-2.3943383410.1%
 
-2.38051123910.1%
 
-2.31459036110.1%
 
ValueCountFrequency (%) 
3.56658034710.1%
 
3.32621206210.1%
 
2.81371760310.1%
 
2.7294461410.1%
 
2.71482070910.1%
 
2.67865806310.1%
 
2.59881218310.1%
 
2.52456791110.1%
 
2.49650285410.1%
 
2.42339560110.1%
 

X7
Real number (ℝ)

UNIQUE

Distinct1000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.02464821318
Minimum-3.86364721
Maximum3.315028017
Zeros0
Zeros (%)0.0%
Memory size7.9 KiB
2020-12-15T21:11:32.238437image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum-3.86364721
5-th percentile-1.644515982
Q1-0.7347431679
median0.005587346778
Q30.7945705533
95-th percentile1.727122461
Maximum3.315028017
Range7.178675227
Interquartile range (IQR)1.529313721

Descriptive statistics

Standard deviation1.04967556
Coefficient of variation (CV)42.58627398
Kurtosis-0.1794586547
Mean0.02464821318
Median Absolute Deviation (MAD)0.763322831
Skewness-0.03910607893
Sum24.64821318
Variance1.101818781
MonotocityNot monotonic
2020-12-15T21:11:32.462509image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
-0.489408834110.1%
 
0.491851892110.1%
 
1.52773079110.1%
 
1.26979230810.1%
 
2.22141062710.1%
 
0.359193939310.1%
 
-0.041160159210.1%
 
0.0230507652210.1%
 
0.728889410610.1%
 
0.285491901110.1%
 
-0.995161910210.1%
 
0.855609770210.1%
 
0.673636433410.1%
 
0.483659652210.1%
 
-1.35830470610.1%
 
0.769464548810.1%
 
-0.178909976110.1%
 
-1.85725827110.1%
 
-0.699633569410.1%
 
0.0098520369910.1%
 
-1.69775137710.1%
 
-1.79736477610.1%
 
2.08832189310.1%
 
1.3045016510.1%
 
1.3737352410.1%
 
Other values (975)97597.5%
 
ValueCountFrequency (%) 
-3.8636472110.1%
 
-3.29397329610.1%
 
-2.73899245910.1%
 
-2.7207374710.1%
 
-2.56894494810.1%
 
-2.54606039110.1%
 
-2.5240807510.1%
 
-2.51426294810.1%
 
-2.47590737410.1%
 
-2.44554418610.1%
 
ValueCountFrequency (%) 
3.31502801710.1%
 
2.79649926410.1%
 
2.73763032710.1%
 
2.61829033810.1%
 
2.55135919110.1%
 
2.53842649710.1%
 
2.45360770710.1%
 
2.45129827710.1%
 
2.36486009610.1%
 
2.29464799710.1%
 

X8
Real number (ℝ)

UNIQUE

Distinct1000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.01358996652
Minimum-3.021316784
Maximum3.263740334
Zeros0
Zeros (%)0.0%
Memory size7.9 KiB
2020-12-15T21:11:32.696872image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum-3.021316784
5-th percentile-1.657165153
Q1-0.6114601677
median0.02101568577
Q30.7171718736
95-th percentile1.635931899
Maximum3.263740334
Range6.285057118
Interquartile range (IQR)1.328632041

Descriptive statistics

Standard deviation1.002208907
Coefficient of variation (CV)73.74623807
Kurtosis-0.03071928321
Mean0.01358996652
Median Absolute Deviation (MAD)0.6617306082
Skewness-0.04546847229
Sum13.58996652
Variance1.004422693
MonotocityNot monotonic
2020-12-15T21:11:32.908715image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
-0.362528263510.1%
 
-0.43254798910.1%
 
-0.236013469310.1%
 
0.84480683110.1%
 
0.836238705610.1%
 
-0.466956630810.1%
 
0.0395392596210.1%
 
-0.0860536847110.1%
 
-0.179119056510.1%
 
-0.0372384544810.1%
 
-0.982505341710.1%
 
-1.38504250510.1%
 
-0.078600515710.1%
 
1.07730156110.1%
 
0.848911122510.1%
 
-1.58795589110.1%
 
-1.76334319810.1%
 
1.3337720410.1%
 
0.658882933310.1%
 
-1.19089001610.1%
 
0.0514590033110.1%
 
-1.75006370510.1%
 
-0.723236330810.1%
 
-1.08468553810.1%
 
-0.674114084310.1%
 
Other values (975)97597.5%
 
ValueCountFrequency (%) 
-3.02131678410.1%
 
-2.86512313910.1%
 
-2.70094826610.1%
 
-2.66034373510.1%
 
-2.56190214510.1%
 
-2.53871586610.1%
 
-2.47012607110.1%
 
-2.45730020910.1%
 
-2.41879857810.1%
 
-2.40336484310.1%
 
ValueCountFrequency (%) 
3.26374033410.1%
 
2.69100826110.1%
 
2.66832601810.1%
 
2.6273430510.1%
 
2.54234447710.1%
 
2.50096465210.1%
 
2.47740862710.1%
 
2.41577986310.1%
 
2.38381339310.1%
 
2.37265043210.1%
 

X9
Real number (ℝ)

UNIQUE

Distinct1000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.005644363307
Minimum-3.514554213
Maximum3.165321063
Zeros0
Zeros (%)0.0%
Memory size7.9 KiB
2020-12-15T21:11:33.139386image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum-3.514554213
5-th percentile-1.64619871
Q1-0.7070576871
median0.001565408017
Q30.69923742
95-th percentile1.735915952
Maximum3.165321063
Range6.679875276
Interquartile range (IQR)1.406295107

Descriptive statistics

Standard deviation1.014663539
Coefficient of variation (CV)179.7658096
Kurtosis-0.08573338138
Mean0.005644363307
Median Absolute Deviation (MAD)0.7019536773
Skewness-0.02278058149
Sum5.644363307
Variance1.029542098
MonotocityNot monotonic
2020-12-15T21:11:33.353446image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
0.661080230710.1%
 
0.481953265810.1%
 
-0.26412521710.1%
 
-1.07898959210.1%
 
-0.854534334410.1%
 
-0.439121439910.1%
 
-1.26946061310.1%
 
1.73304777210.1%
 
-0.680938183510.1%
 
0.279005473510.1%
 
0.82382450410.1%
 
1.03842299310.1%
 
-0.55901117310.1%
 
-0.79618569110.1%
 
1.56755075210.1%
 
0.381858741710.1%
 
-0.261373096210.1%
 
-0.538805007110.1%
 
-0.31930648410.1%
 
-0.423958129910.1%
 
-0.496497068810.1%
 
-0.139325175810.1%
 
1.16209732610.1%
 
1.94610933710.1%
 
-0.146458720710.1%
 
Other values (975)97597.5%
 
ValueCountFrequency (%) 
-3.51455421310.1%
 
-3.11598292610.1%
 
-2.9657235910.1%
 
-2.88436455910.1%
 
-2.75918563110.1%
 
-2.68485467610.1%
 
-2.57953776410.1%
 
-2.45417993210.1%
 
-2.34593176810.1%
 
-2.34080462310.1%
 
ValueCountFrequency (%) 
3.16532106310.1%
 
2.43453984510.1%
 
2.43033164310.1%
 
2.40720377510.1%
 
2.38774148310.1%
 
2.36676455210.1%
 
2.35744178810.1%
 
2.32913849710.1%
 
2.31620571410.1%
 
2.27741912410.1%
 

y
Boolean

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
1
500 
0
500 
ValueCountFrequency (%) 
150050.0%
 
050050.0%
 
2020-12-15T21:11:33.507036image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Interactions

2020-12-15T21:11:06.286658image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:11:06.496664image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:11:06.710251image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:11:06.920454image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:11:07.133832image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:11:07.342996image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:11:07.549873image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:11:07.917916image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:11:08.254653image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:11:08.528555image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:11:08.741560image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:11:08.960188image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:11:09.172499image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:11:09.382960image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:11:09.595936image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:11:09.808842image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:11:10.023415image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:11:10.238224image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:11:10.443022image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:11:10.655950image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:11:10.864488image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:11:11.074516image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:11:11.288157image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:11:11.485600image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:11:11.697577image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:11:11.909628image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:11:12.124247image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:11:12.339445image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:11:12.549591image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:11:12.758687image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:11:12.966745image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:11:13.166881image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:11:13.378675image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:11:13.593531image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:11:13.800632image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:11:14.012563image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:11:14.370347image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:11:14.589194image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:11:14.802552image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:11:15.005988image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:11:15.220450image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:11:15.427603image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:11:15.638227image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:11:15.841342image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:11:16.056951image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:11:16.278537image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:11:16.490031image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:11:16.703606image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:11:16.913144image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:11:17.123062image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:11:17.340444image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:11:17.560517image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:11:17.778392image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:11:17.979416image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:11:18.185736image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:11:18.394493image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:11:18.607527image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:11:18.815249image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:11:19.046258image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:11:19.266215image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:11:19.481580image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:11:19.691484image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:11:19.901136image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:11:20.114171image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:11:20.325914image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:11:20.669336image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:11:20.876193image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:11:21.073946image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:11:21.292022image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:11:21.502728image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:11:21.714635image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:11:21.932312image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:11:22.152009image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:11:22.372329image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:11:22.589087image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:11:22.808434image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:11:23.028617image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:11:23.257482image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:11:23.491475image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:11:23.705510image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:11:23.931737image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:11:24.137334image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:11:24.346682image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:11:24.553293image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:11:24.755507image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:11:24.964805image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:11:25.171755image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:11:25.388132image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:11:25.601664image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:11:25.808158image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:11:26.016397image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:11:26.218693image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:11:26.430922image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:11:26.636773image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:11:26.982485image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:11:27.196009image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:11:27.403764image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:11:27.613862image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:11:27.825796image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:11:28.034023image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Correlations

2020-12-15T21:11:33.613959image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2020-12-15T21:11:33.882491image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2020-12-15T21:11:34.296336image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2020-12-15T21:11:34.580750image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Missing values

2020-12-15T21:11:28.386677image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:11:28.766582image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Sample

First rows

X0X1X2X3X4X5X6X7X8X9y
0-0.0522130.338963-2.8275440.224669-1.8090940.2901210.8336011.7875781.190428-0.6998160
1-0.324563-0.271444-1.047632-2.1535461.1420210.615576-1.0986900.186790-0.999461-0.8712020
20.5958290.082149-0.036141-1.536773-0.6107300.1496930.0136672.191303-0.036883-0.3674501
3-1.094319-0.6224390.4280781.641097-1.912682-0.4094500.022356-0.883685-1.0430960.9679300
4-0.3619551.685080-0.820187-0.074589-0.482351-0.3816272.5245680.054192-0.5066370.3818590
50.6368780.0325161.3369531.480155-0.212712-0.899852-0.667880-0.270838-1.106451-0.8690990
60.205964-0.087310-1.592303-0.9771491.199311-1.262685-0.9183820.8320291.1260811.0160230
70.980844-1.0125061.4180210.3088340.472456-0.424218-1.372861-2.085444-0.7248900.5880171
8-0.809907-0.560338-0.306753-0.180044-1.377055-0.745737-0.144210-1.0736911.9347950.0152660
9-0.5594371.0348360.6469240.0884580.9368140.141137-1.078354-0.510947-0.9236111.1133700

Last rows

X0X1X2X3X4X5X6X7X8X9y
9901.0293670.3739720.5038270.2876761.1725520.710175-1.1545241.157147-0.1496770.2323540
9910.5982630.0331952.400693-2.6442550.2697290.5458300.0768890.703953-0.850807-0.4833261
992-1.981646-0.188565-0.370516-1.233063-0.7473451.105309-0.6110121.1984671.206820-1.2968400
993-0.5366571.201859-0.199363-0.448479-0.0845241.0146151.289632-0.744051-0.6016022.0596080
9940.0890610.0406060.8365520.9882400.472866-0.314131-1.0757490.735188-1.079054-2.9657240
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